Role of Cardiac Energetics in Aortic Stenosis Disease Progression: Identifying the High-risk Metabolic Phenotype

Background: Severe aortic stenosis (AS) is associated with left ventricular (LV) hypertrophy and cardiac metabolic alterations with evidence of steatosis and impaired myocardial energetics. Despite this common phenotype, there is an unexplained and wide individual heterogeneity in the degree of hypertrophy and progression to myocardial fibrosis and heart failure. We sought to determine whether the cardiac metabolic state may underpin this variability. Methods: We recruited 74 asymptomatic participants with AS and 13 healthy volunteers. Cardiac energetics were measured using phosphorus spectroscopy to define the myocardial phosphocreatine to adenosine triphosphate ratio. Myocardial lipid content was determined using proton spectroscopy. Cardiac function was assessed by cardiovascular magnetic resonance cine imaging. Results: Phosphocreatine/adenosine triphosphate was reduced early and significantly across the LV wall thickness quartiles (Q2, 1.50 [1.21–1.71] versus Q1, 1.64 [1.53–1.94]) with a progressive decline with increasing disease severity (Q4, 1.48 [1.18–1.70]; P=0.02). Myocardial triglyceride content levels were overall higher in all the quartiles with a significant increase seen across the AV pressure gradient quartiles (Q2, 1.36 [0.86–1.98] versus Q1, 1.03 [0.81–1.56]; P=0.034). While all AS groups had evidence of subclinical LV dysfunction with impaired strain parameters, impaired systolic longitudinal strain was related to the degree of energetic impairment (r=0.219; P=0.03). Phosphocreatine/adenosine triphosphate was not only an independent predictor of LV wall thickness (r=−0.20; P=0.04) but also strongly associated with myocardial fibrosis (r=−0.24; P=0.03), suggesting that metabolic changes play a role in disease progression. The metabolic and functional parameters showed comparable results when graded by clinical severity of AS. Conclusions: A gradient of myocardial energetic deficit and steatosis exists across the spectrum of hypertrophied AS hearts, and these metabolic changes precede irreversible LV remodeling and subclinical dysfunction. As such, cardiac metabolism may play an important and potentially causal role in disease progression.


SUPPLEMENTARY MATERIAL
LV Pressure Gradient quartiles analysis 87 participants were divided into quartiles based on total LV gradient (LVG = AV gradient + systolic blood pressure).

Demographic and clinical characteristics
Participants in Q1 were relatively younger (mean age 55 ± 13 years) with lower average systolic BP (124 ± 10 mmHg).All quartiles were matched in rest of the characteristics with no significant difference in blood glucose, total cholesterol, and triglyceride levels.Notably there was no difference in FFA levels across the quartiles.

Myocardial Fibrosis on T1 mapping, ECV and LGE:
T1 and ECV: No significant trend was seen in myocardial T1 values and ECV across the LVG groups.Native T1 and ECV were low normal in Q1-3 and then increased in Q4 (1176 ± 74 ms, Q4 vs 1120 ± 29 ms, Q1; Table S5).
Thus, both the pressure gradient analysis indicate that the presence of myocardial steatosis is related to degree of pressure overload.These metabolic changes are predominantly driven by the AV gradient and not the total LV gradient.LV wall thickness (LVWT) increased across the MV quartiles, and cardiac energetics were reduced at a wall thicknes~14mm in the MV quartile data, but the trend was non-significant.In regression analysis, LVWT rather than mass/volume ratio was the significant variable.Table S1:

Figure S2 :
Figure S2: Cardiac metabolic parameters across the normal controls and clinical grades of AS.P values are derived using ordered medians Jonckheere-Terpstra test from linear regression analysis for the study groups.P values and R values are from

Figure S3 :
Figure S3: Correlation analysis: Cardiac metabolism and LV wall thickness (LVWT) as continuous variables across the whole study cohort.

Figure S4 :
Figure S4: Correlation analysis: Cardiac metabolism and aortic valve gradient (AVG) as continuous variables across the whole study cohort.

Figure S5 :
Figure S5: Mass/Volume (MV) quartiles analysis (p>0.05 for all analysis) Demographics, clinical, biochemical characteristics and CMR indices of cardiac structure, function and metabolism in group based on LVWT.Values are mean ± SD for continuous data unless stated otherwise and counts (percentages) for categorical data.P values are from ordinary one-way ANOVA for demographic, clinical and biochemical parameters.For cardiac structure and function, P values are for 1-way ANOVA with post hoc Bonferroni correction.*For cardiac metabolism, median and IQR are reported, and p values are the result of Jonckheere-Terpstra test across the groups from linear regression analysis (<0.05 significant in bold).LGE and medications were assessed as categorical variables.For all tables, AS indicates aortic stenosis; BMI, body mass index; SBP, systolic blood pressure; DBP, Diastolic blood pressure; AF, atrial fibrillation; FFA, free fatty acids; TC, total cholesterol; TG, Triglycerides; BNP, brain natriuretic peptide; ARB, Angiotensin Receptor Blockers; ACE-I, Angiotensin Converting Enzyme Inhibitors.AVG, aortic valve gradient; AVA, aortic valve area; LV, left ventricle; EDV, enddiastolic volume; ESV, end-systolic volume; SV, stroke volume; long, longitudinal; circ, circumferential; SR, strain rate; LA, left atrium; RV, right ventricle; LGE, late gadolinium enhancement; ECV, extracellular volume; MTG, myocardial triglyceride content; PCr/ATP, Phosphocreatine/ adenosine triphosphate ratio.Table S2: Partial correlation analysis: LVWT and characteristics of cardiac structure, function and metabolism when controlled for aortic valve gradient (AVG) alone and AVG + Age + BMI (Body mass index).P <0.05 significant derived using Spearman's partial correlation analysis.Table S3: Demographics, clinical, biochemical characteristics and CMR indices of cardiac structure, function and metabolism in group based on peak AV gradient.Values are mean ± SD for continuous data unless stated otherwise and counts (percentages) for categorical data.P values are from ordinary one-way ANOVA for demographic, clinical and biochemical parameters.For cardiac structure and function, P values are for 1-way ANOVA with post hoc Bonferroni correction.*For cardiac metabolism, median and IQR are reported, and p values reported are the result of Jonckheere-Terpstra test across the groups from linear regression analysis (<0.05 significant in bold).LGE and medications were assessed as categorical variables.TableS4: Partial correlation analysis: Aortic valve gradient and characteristics of cardiac structure, function and metabolism when controlled for left ventricular wall thickness.P < 0.05 significant, derived using Spearman's partial correlation method.Table S5: Demographics, clinical, biochemical characteristics and CMR indices of cardiac structure, function and metabolism in group based on total LV gradient.Values are mean ± SD for continuous data unless started otherwise and counts (percentages) for categorical data.P values are from ordinary one-way ANOVA for demographic, clinical and biochemical parameters.For cardiac structure and function, P values are for 1-way ANOVA with post hoc Bonferroni correction.*For cardiac metabolism, median and IQR are reported, and p values reported are the result of Jonckheere-Terpstra test across the groups from linear regression analysis (<0.05 significant in bold).LGE and medications were assessed as categorical variables.Table S6: Correlation analysis: Total left ventricular gradient and characteristics of cardiac structure, function and metabolism when controlled for left ventricular wall thickness.P < 0.05 significant.Table S7: Demographics, clinical, biochemical characteristics and CMR indices of cardiac structure, function and metabolism in group based on clinical grading of AS.Values are mean ± SD for continuous data unless stated otherwise and counts (percentages) for categorical data.P values are from ordinary one-way ANOVA for demographic, clinical and biochemical parameters.For cardiac structure and function, P values are for 1-way ANOVA with post hoc Bonferroni correction.*For cardiac metabolism, median and IQR are reported, and p values are the result of Jonckheere-Terpstra test across the groups from linear regression analysis (<0.05 significant in bold).LGE and medications were assessed as categorical variables.
P values for demographic, clinical and biochemical parameters were generated using ordinary one-wayANOVA comparison, andthose for AV/LV and Other parameters were generated using one-way ANOVA comparison with post hoc Bonferroni correction.Medications has categorical variables; hence they were compared using ttests and each quartile data detailed as counts (percentages) format.LGE was a categorical variable based on presence or absence, hence data were compared using t-tests and each quartile data detailed here in counts (percentages) format.*Cardiac metabolism data was not normally distributed; p values were generated by comparing ordered medians using Jonckheere-Terpstra test.Data for each quartile is, thus, represented as median (IQR).Significant (p<0.05)values are highlighted in bold.P values for demographic, clinical and biochemical parameters were generated using ordinary one-way ANOVA comparison, and those for AV/LV and Other parameters were generated using one-way ANOVA comparison with post hoc Bonferroni correction.Medications has categorical variables; hence they were compared using ttests and each quartile data detailed as counts (percentages) format.LGE was a categorical variable based on presence or absence, hence data were compared using t-tests and each quartile data detailed here in counts (percentages) format.*Cardiac metabolism data was not normally distributed; p values were generated by comparing ordered medians using Jonckheere-Terpstra test.Data for each quartile is, thus, represented as median (IQR).Significant (p<0.05)values are highlighted in bold.counts (percentages) format.*Cardiac metabolism data was not normally distributed; p values were generated by comparing ordered medians using Jonckheere-Terpstra test.Data for each quartile is, thus, represented as median (IQR).Significant (p<0.05)values are highlighted in bold.